August 2015
Intermediate to advanced
272 pages
5h 46m
Japanese
Content preview from Think Stats 第2版 ―プログラマのための統計入門
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101
101
7.7 スピアマンの順位相関
実世界のほとんどの相関は完全ではありませんが、それでも役に立ちます。身長と
体重の相関は、
0.51
で、同様の人間に関する変数と比較すると、強い相関になります。
7.6
非線形関係
ピアソンの相関係数が
0
に近ければ、変数間に何の関係もないと結論付けたくなり
ますが、その結論は妥当ではありません。ピアソンの相関係数は線形（
linear
）な関
係のみの指標です。変数間に非線形な関係があると、ρはその強さを反映できません。
図
7-4
は、
http://wikipedia.org/wiki/Correlation_and_dependence
から取られた
ものです。これは注意深く作られたデータセットの散布図と相関係数を示しています。
図
7-4
さまざまな相関のデータセットの例
一番上の列はさまざまな相関係数に対する線形相関の例を示しています。これから、
ρの値が異なるとどのような相関になるかがわかります。
2
番目の列はさまざまな傾
きを持つ完全な相関を示します。傾きは相関に関係ないことがわかります（傾きの推
定についてはすぐあとで説明します）。
3
番目の列は、明らかな相関があるものの、
非線形なので相関係数が
0
になるようなデータセットを示しています。
この話の教訓は、やみくもに相関係数を求めるのではなく、その前にいつもデータ
の散布図を見るべきだ、ということです。
7.7
スピアマンの順位相関
ピアソンの相関係数は変数間の相関が線形で、分布がほぼ正規分布ならば、うまく
102
7 章 変数間の関係 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.